Yang, S. , Lemke, C. , Cox, B. F., Newton, I. P., Näthke, I. and Cochran, S. (2021) A learning based microultrasound system for the detection of inflammation of the gastrointestinal tract. IEEE Transactions on Medical Imaging, 40(1), pp. 38-47. (doi: 10.1109/TMI.2020.3021560)
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222580.pdf - Accepted Version 1MB |
Abstract
Inflammation of the gastrointestinal (GI) tract accompanies several diseases, including Crohn’s disease. Currently, video capsule endoscopy and deep bowel enteroscopy are the main means for direct visualisation of the bowel surface. However, the use of optical imaging limits visualisation to the luminal surface only, which makes early-stage diagnosis difficult. In this study, we propose a learning enabled microultrasound (μUS) system that aims to classify inflamed and non-inflamed bowel tissues. μUS images of the caecum, small bowel and colon were obtained from mice treated with agents to induce inflammation. Those images were then used to train three deep learning networks and to provide a ground truth of inflammation status. The classification accuracy was evaluated using 10-fold evaluation and additional B-scan images. Our deep learning approach allowed robust differentiation between healthy tissue and tissue with early signs of inflammation that is not detectable by current endoscopic methods or by human inspection of the μUS images. The methods may be a foundation for future early GI disease diagnosis and enhanced management with computer-aided imaging.
| Item Type: | Articles |
|---|---|
| Status: | Published |
| Refereed: | Yes |
| Glasgow Author(s) Enlighten ID: | Cochran, Professor Sandy and Lemke, Dr Christina and Yang, Dr Shufan and Cox, Dr Benjamin F |
| Authors: | Yang, S., Lemke, C., Cox, B. F., Newton, I. P., Näthke, I., and Cochran, S. |
| College/School: | College of Science and Engineering > School of Engineering College of Science and Engineering > School of Engineering > Systems Power and Energy |
| Journal Name: | IEEE Transactions on Medical Imaging |
| Publisher: | IEEE |
| ISSN: | 0278-0062 |
| ISSN (Online): | 1558-254X |
| Published Online: | 03 September 2020 |
| Copyright Holders: | Copyright © 2019 IEEE |
| First Published: | First published in IEEE Transactions on Medical Imaging 40(1): 38-47 |
| Publisher Policy: | Reproduced in accordance with the copyright policy of the publisher |
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